The demands on wireless communication capabilities in today's society are increasing rapidly. In particular, fast and easily accessible communication is desired through hand-held devices over large areas. It is particularly challenging to achieve such communication for mobile devices which are moving, e.g. when moving over large distances with poor network coverage or when affected by unknown sources of noise interrupting a signal for communication. In particular, if a client, being for example a mobile phone, moves over large areas the client has to connect to several base stations in order to maintain a sufficient connection for communication.
The mobile nature of a client with respect to the base stations may introduce several potential sources of communication performance degradation. Such sources may derive from complex terrain, competition for available channels, or the source may be an unknown source of noise related to e.g. radio-frequency interference.
Diagnosing and identifying the sources causing performance degradation is desirable in order to solving the problems and for providing improved communication quality. Measurement of the signal strength from a client may be used for simpler measurements, such as finding areas of poor network coverage. However, problems of more complex nature are more difficult to detect. There may for example be problems related to the base stations and/or clients themselves, and/or more inconsistent sources of radio-frequency interference which are not straight-forward to identify and/or diagnose.
Thus, a drawback of prior art solutions is that they are incapable of reliably identifying problems at hardware (e.g. a base station) because the information related to the signal strength is obtained via the hardware itself.
Another drawback is that more complex sources of noise or disturbances, e.g. being inconsistent in time, are difficult to identify due to unknown and/or unpredictable times of presence of the source.